About the reviewers
Armando Fandango creates AI-powered products by leveraging his
expertise in deep learning, machine learning, distributed computing, and
computational methods. He advises Owen.ai Inc., Real Engagement, and
Loyalty Inc. on AI product strategy. He founded NeuraSights to create
insights using neural networks. He was the chief data scientist and CTO for
Epic Engg., Consulting Group LLC, and director of data science for Sonobi.
He has advised high-tech startups as an AI expert and advisory board
member.
Nicolas Guet is a financial controller at GRDF. He was a project leader for
ENGIE and a SAP BI consultant for Capgemini.
He graduated from Université Pierre et Marie Curie (Paris VI) and Université
Paris Sud (Paris XI). He also designed a decision-making tool in Java that
was part of an AI Advanced Planning System, managing hundreds of
thousands of orders for 100+ suppliers worldwide. He is dedicated to
promoting sustainable energy and smart grids.
Jérémie Rothman is an IT project manager at the French National Forest
Office (ONF). He was an IT consultant for TCS France and worked on a
Total SA route optimizing project. He graduated from Université Paris 1
Panthéon Sorbonne in economics and holds a degree in software mathematics
(Université Paris 5 René Descartes).
He designed a Nash equilibrium theory of games algorithm to optimize
warehouse locations for an AI Advanced Planning System (APS). The APS
program is used to this day.

About the author
Denis Rothman graduated from l’Université Paris-Sorbonne and l’Université
Paris-Diderot, writing one of the very first word2matrix embedding solutions.
He began his career authoring one of the first AI cognitive NLP chatbots
applied as a language teacher for Moët et Chandon and other companies. He
authored an AI resource optimizer for IBM and apparel producers. He then
authored an Advanced Planning and Scheduling (APS) solution used
worldwide.
I want to thank the corporations who trusted me from the start to deliver artificial intelligence solutions and share the
risks of continuous innovation. I also thank my family, who believed I would make it big at all times.

Contents
1:Become an Adaptive Thinker
2:Thinklike a Machine
3:Apply Machine Thinking to a Human Problem
4:Become an Unconventional lnnovator
5:Manage the Power of Machine Learning and Deep
Learning
6:Don’t Get Lost in Techniques-Focus on
Optimizing Your Solutions
7:When and How to Use Artificial Inteligence
8:Revolutions Designed for Some Corporations and
Disruptive Innovations for Small to Large
Companies
9:Getting Your Neurons to Work
10:Applying Biomimicking to Artificial lntelligence
11:Conceptual Representation Learning
12:Automated Planning and Scheduling
13:Al and the Internet of Things(loT)
14:Optimizing Blockchains withAl
15:Cognitive NLP Chatbots
16:Improve the Emotional Intelligence Deficiencies
of Chatbots
17:Quantum Computers That Think
AppendixA:Answers to the Questions
Appendix B:Index